#include "Feature.h"
#include "internal/FrameHessian.h"
#include "frontend/FeatureDetector.h"

#include <opencv2/opencv.hpp>

namespace ldso {
    extern int bit_pattern_31_[256 * 4];   // forward declare

    FeatureDetector::FeatureDetector() {

        // compute umax
        umax.resize(HALF_PATCH_SIZE + 1);

        int v, v0, vmax = cvFloor(HALF_PATCH_SIZE * sqrt(2.f) / 2 + 1);
        int vmin = cvCeil(HALF_PATCH_SIZE * sqrt(2.f) / 2);
        const double hp2 = HALF_PATCH_SIZE * HALF_PATCH_SIZE;
        for (v = 0; v <= vmax; ++v)
            umax[v] = cvRound(sqrt(hp2 - v * v));

        // Make sure we are symmetric
        for (v = HALF_PATCH_SIZE, v0 = 0; v >= vmin; --v) {
            while (umax[v0] == umax[v0 + 1])
                ++v0;
            umax[v] = v0;
            ++v0;
        }
    }

    FeatureDetector::~FeatureDetector() {

    }

    int FeatureDetector::DetectCorners(int nFeatures, shared_ptr<Frame> &frame) {

        // grid it
        int gridsize = int(sqrtf(wG[0] * hG[0] / nFeatures) + 0.5);
        int gridX = wG[0] / gridsize + 1, gridY = hG[0] / gridsize + 1;
        float nfeatInGrid = float(nFeatures) / (wG[0] * hG[0]) * (gridsize * gridsize);

        float maxScore = 0, scoreTH = 0;
        int skip = (HALF_PATCH_SIZE * 2 / gridsize) + 1;

        for (int gx = skip; gx < gridX - skip; gx++) {  // 最边上的不要
            for (int gy = skip; gy < gridY - skip; gy++) {

                float maxGrad = 0, gradTH = 0;
                float *gradData = &frame->frameHessian->absSquaredGrad[0][gy * gridsize * wG[0] + gx * gridsize];

                for (int x = 0; x < gridsize; x++) {
                    for (int y = 0; y < gridsize; y++) {
                        if (gradData[y * wG[0] + x] > maxGrad)
                            maxGrad = gradData[y * wG[0] + x];
                    }
                }

                vector<pair<int, float>> candidate;

                gradTH = (0.5 * maxGrad) > 5 ? 0.5 * maxGrad : 5;
                int picked = 0;

                for (int x = 0; x < gridsize; x++) {
                    for (int y = 0; y < gridsize; y++) {
                        int idx = y * gridsize + x;
                        if (gradData[y * wG[0] + x] > gradTH) {
                            // this is an candidate
                            int realX = gx * gridsize + x, realY = gy * gridsize + y;
                            float s = ShiTomasiScore(frame, realX, realY);
                            candidate.push_back(pair<int, float>(idx, s));
                            if (s > maxScore) {
                                maxScore = s;
                            }

                        }
                    }
                }

                sort(candidate.begin(), candidate.end(),
                     [](const pair<int, float> &p1, const pair<int, float> &p2) { return p1.second > p2.second; });

                for (auto &p: candidate) {
                    int x = p.first % gridsize;
                    int y = p.first / gridsize;
                    int realX = gx * gridsize + x, realY = gy * gridsize + y;
                    shared_ptr<Feature> feat(new Feature(realX, realY, frame));
                    feat->score = p.second;
                    frame->features.push_back(feat);
                    picked++;

                    if (picked > (nfeatInGrid))
                        break;
                }
                // LOG(INFO) << "picked " << picked << "/" << nfeatInGrid << " in one grid" << endl;
            }
        }

        // find the corners
        scoreTH = 0.01 * maxScore;
        vector<shared_ptr<Feature>> corners;
        for (auto &feat: frame->features) {
            if (feat->score > scoreTH) {
                feat->isCorner = true;
                corners.push_back(feat);
            }
        }

        for (int i = 0; i < corners.size(); i++) {
            for (int j = i + 1; j < corners.size(); j++) {
                auto &feat1 = corners[i], feat2 = corners[j];
                if ((feat1->uv - feat2->uv).norm() < 5) {
                    if (feat1->score > feat2->score)
                        feat2->isCorner = false;
                    else
                        feat1->isCorner = false;
                }

            }
        }

        int cntCornerSelected = 0;
        for (auto &feat: frame->features) {
            if (feat->isCorner) {
                feat->angle = IC_Angle(
                        frame->frameHessian->dIp[feat->level], Vec2f(feat->uv[0], feat->uv[1]), feat->level);
                ComputeDescriptor(frame, feat);
                cntCornerSelected++;
            }
        }
        return cntCornerSelected;
    }

    int FeatureDetector::ComputeDescriptor(shared_ptr<Frame> &frame, shared_ptr<Feature> feat) {

        const float factorPI = (float) (CV_PI / 180.f);

        float angle = feat->angle * factorPI;
        float a = (float) cosf(angle), b = (float) sinf(angle);
        Vec3f *img = frame->frameHessian->dIp[feat->level];

        int level = 0;
        float ul = feat->uv[0];
        float vl = feat->uv[1];

        while (level < feat->level) {
            ul *= 0.5;
            vl *= 0.5;
            level++;
        }

        const Vec3f *center = img + (int(vl) * wG[feat->level] + (int) ul);

        const int step = wG[feat->level];

        int *pattern = bit_pattern_31_;
#define GET_VALUE(idx) \
        center[int(pattern[idx]*b + pattern[idx+1]*a)*step + int(pattern[idx]*a - pattern[idx+1]*b)][0]

        for (int i = 0; i < 32; ++i, pattern += 32) {
            int t0, t1, val;
            t0 = GET_VALUE(0);
            t1 = GET_VALUE(2);
            val = t0 < t1;
            t0 = GET_VALUE(4);
            t1 = GET_VALUE(6);
            val |= (t0 < t1) << 1;
            t0 = GET_VALUE(8);
            t1 = GET_VALUE(10);
            val |= (t0 < t1) << 2;
            t0 = GET_VALUE(12);
            t1 = GET_VALUE(14);
            val |= (t0 < t1) << 3;
            t0 = GET_VALUE(16);
            t1 = GET_VALUE(18);
            val |= (t0 < t1) << 4;
            t0 = GET_VALUE(20);
            t1 = GET_VALUE(22);
            val |= (t0 < t1) << 5;
            t0 = GET_VALUE(24);
            t1 = GET_VALUE(26);
            val |= (t0 < t1) << 6;
            t0 = GET_VALUE(28);
            t1 = GET_VALUE(30);
            val |= (t0 < t1) << 7;

            feat->descriptor[i] = (uchar) val;
        }
#undef GET_VALUE
        return 0;
    }

    void FeatureDetector::DrawFeatures(shared_ptr<Frame> &frame, const string &windowName) {

        cv::Mat img(hG[0], wG[0], CV_8UC3);   // color image displayed
        for (int idx = 0; idx < wG[0] * hG[0]; idx++) {
            img.data[idx * 3 + 0] = frame->frameHessian->dI[idx][0] > 255 ? 255 : frame->frameHessian->dI[idx][0];
            img.data[idx * 3 + 1] = img.data[idx * 3 + 0];
            img.data[idx * 3 + 2] = img.data[idx * 3 + 0];
        }

        for (auto &feat: frame->features) {
            if (feat->isCorner) {
                cv::circle(img, cv::Point2f(feat->uv[0], feat->uv[1]), 1, cv::Scalar(0, 250, 0), 1);
            } else {
                cv::circle(img, cv::Point2f(feat->uv[0], feat->uv[1]), 1, cv::Scalar(0, 0, 250), 1);
            }
        }

        cv::imshow(windowName, img);
        cv::waitKey(0);
    }

    // ORB-pattern
    int bit_pattern_31_[256 * 4] =
            {
                    8, -3, 9, 5/*mean (0), correlation (0)*/,
                    4, 2, 7, -12/*mean (1.12461e-05), correlation (0.0437584)*/,
                    -11, 9, -8, 2/*mean (3.37382e-05), correlation (0.0617409)*/,
                    7, -12, 12, -13/*mean (5.62303e-05), correlation (0.0636977)*/,
                    2, -13, 2, 12/*mean (0.000134953), correlation (0.085099)*/,
                    1, -7, 1, 6/*mean (0.000528565), correlation (0.0857175)*/,
                    -2, -10, -2, -4/*mean (0.0188821), correlation (0.0985774)*/,
                    -13, -13, -11, -8/*mean (0.0363135), correlation (0.0899616)*/,
                    -13, -3, -12, -9/*mean (0.121806), correlation (0.099849)*/,
                    10, 4, 11, 9/*mean (0.122065), correlation (0.093285)*/,
                    -13, -8, -8, -9/*mean (0.162787), correlation (0.0942748)*/,
                    -11, 7, -9, 12/*mean (0.21561), correlation (0.0974438)*/,
                    7, 7, 12, 6/*mean (0.160583), correlation (0.130064)*/,
                    -4, -5, -3, 0/*mean (0.228171), correlation (0.132998)*/,
                    -13, 2, -12, -3/*mean (0.00997526), correlation (0.145926)*/,
                    -9, 0, -7, 5/*mean (0.198234), correlation (0.143636)*/,
                    12, -6, 12, -1/*mean (0.0676226), correlation (0.16689)*/,
                    -3, 6, -2, 12/*mean (0.166847), correlation (0.171682)*/,
                    -6, -13, -4, -8/*mean (0.101215), correlation (0.179716)*/,
                    11, -13, 12, -8/*mean (0.200641), correlation (0.192279)*/,
                    4, 7, 5, 1/*mean (0.205106), correlation (0.186848)*/,
                    5, -3, 10, -3/*mean (0.234908), correlation (0.192319)*/,
                    3, -7, 6, 12/*mean (0.0709964), correlation (0.210872)*/,
                    -8, -7, -6, -2/*mean (0.0939834), correlation (0.212589)*/,
                    -2, 11, -1, -10/*mean (0.127778), correlation (0.20866)*/,
                    -13, 12, -8, 10/*mean (0.14783), correlation (0.206356)*/,
                    -7, 3, -5, -3/*mean (0.182141), correlation (0.198942)*/,
                    -4, 2, -3, 7/*mean (0.188237), correlation (0.21384)*/,
                    -10, -12, -6, 11/*mean (0.14865), correlation (0.23571)*/,
                    5, -12, 6, -7/*mean (0.222312), correlation (0.23324)*/,
                    5, -6, 7, -1/*mean (0.229082), correlation (0.23389)*/,
                    1, 0, 4, -5/*mean (0.241577), correlation (0.215286)*/,
                    9, 11, 11, -13/*mean (0.00338507), correlation (0.251373)*/,
                    4, 7, 4, 12/*mean (0.131005), correlation (0.257622)*/,
                    2, -1, 4, 4/*mean (0.152755), correlation (0.255205)*/,
                    -4, -12, -2, 7/*mean (0.182771), correlation (0.244867)*/,
                    -8, -5, -7, -10/*mean (0.186898), correlation (0.23901)*/,
                    4, 11, 9, 12/*mean (0.226226), correlation (0.258255)*/,
                    0, -8, 1, -13/*mean (0.0897886), correlation (0.274827)*/,
                    -13, -2, -8, 2/*mean (0.148774), correlation (0.28065)*/,
                    -3, -2, -2, 3/*mean (0.153048), correlation (0.283063)*/,
                    -6, 9, -4, -9/*mean (0.169523), correlation (0.278248)*/,
                    8, 12, 10, 7/*mean (0.225337), correlation (0.282851)*/,
                    0, 9, 1, 3/*mean (0.226687), correlation (0.278734)*/,
                    7, -5, 11, -10/*mean (0.00693882), correlation (0.305161)*/,
                    -13, -6, -11, 0/*mean (0.0227283), correlation (0.300181)*/,
                    10, 7, 12, 1/*mean (0.125517), correlation (0.31089)*/,
                    -6, -3, -6, 12/*mean (0.131748), correlation (0.312779)*/,
                    10, -9, 12, -4/*mean (0.144827), correlation (0.292797)*/,
                    -13, 8, -8, -12/*mean (0.149202), correlation (0.308918)*/,
                    -13, 0, -8, -4/*mean (0.160909), correlation (0.310013)*/,
                    3, 3, 7, 8/*mean (0.177755), correlation (0.309394)*/,
                    5, 7, 10, -7/*mean (0.212337), correlation (0.310315)*/,
                    -1, 7, 1, -12/*mean (0.214429), correlation (0.311933)*/,
                    3, -10, 5, 6/*mean (0.235807), correlation (0.313104)*/,
                    2, -4, 3, -10/*mean (0.00494827), correlation (0.344948)*/,
                    -13, 0, -13, 5/*mean (0.0549145), correlation (0.344675)*/,
                    -13, -7, -12, 12/*mean (0.103385), correlation (0.342715)*/,
                    -13, 3, -11, 8/*mean (0.134222), correlation (0.322922)*/,
                    -7, 12, -4, 7/*mean (0.153284), correlation (0.337061)*/,
                    6, -10, 12, 8/*mean (0.154881), correlation (0.329257)*/,
                    -9, -1, -7, -6/*mean (0.200967), correlation (0.33312)*/,
                    -2, -5, 0, 12/*mean (0.201518), correlation (0.340635)*/,
                    -12, 5, -7, 5/*mean (0.207805), correlation (0.335631)*/,
                    3, -10, 8, -13/*mean (0.224438), correlation (0.34504)*/,
                    -7, -7, -4, 5/*mean (0.239361), correlation (0.338053)*/,
                    -3, -2, -1, -7/*mean (0.240744), correlation (0.344322)*/,
                    2, 9, 5, -11/*mean (0.242949), correlation (0.34145)*/,
                    -11, -13, -5, -13/*mean (0.244028), correlation (0.336861)*/,
                    -1, 6, 0, -1/*mean (0.247571), correlation (0.343684)*/,
                    5, -3, 5, 2/*mean (0.000697256), correlation (0.357265)*/,
                    -4, -13, -4, 12/*mean (0.00213675), correlation (0.373827)*/,
                    -9, -6, -9, 6/*mean (0.0126856), correlation (0.373938)*/,
                    -12, -10, -8, -4/*mean (0.0152497), correlation (0.364237)*/,
                    10, 2, 12, -3/*mean (0.0299933), correlation (0.345292)*/,
                    7, 12, 12, 12/*mean (0.0307242), correlation (0.366299)*/,
                    -7, -13, -6, 5/*mean (0.0534975), correlation (0.368357)*/,
                    -4, 9, -3, 4/*mean (0.099865), correlation (0.372276)*/,
                    7, -1, 12, 2/*mean (0.117083), correlation (0.364529)*/,
                    -7, 6, -5, 1/*mean (0.126125), correlation (0.369606)*/,
                    -13, 11, -12, 5/*mean (0.130364), correlation (0.358502)*/,
                    -3, 7, -2, -6/*mean (0.131691), correlation (0.375531)*/,
                    7, -8, 12, -7/*mean (0.160166), correlation (0.379508)*/,
                    -13, -7, -11, -12/*mean (0.167848), correlation (0.353343)*/,
                    1, -3, 12, 12/*mean (0.183378), correlation (0.371916)*/,
                    2, -6, 3, 0/*mean (0.228711), correlation (0.371761)*/,
                    -4, 3, -2, -13/*mean (0.247211), correlation (0.364063)*/,
                    -1, -13, 1, 9/*mean (0.249325), correlation (0.378139)*/,
                    7, 1, 8, -6/*mean (0.000652272), correlation (0.411682)*/,
                    1, -1, 3, 12/*mean (0.00248538), correlation (0.392988)*/,
                    9, 1, 12, 6/*mean (0.0206815), correlation (0.386106)*/,
                    -1, -9, -1, 3/*mean (0.0364485), correlation (0.410752)*/,
                    -13, -13, -10, 5/*mean (0.0376068), correlation (0.398374)*/,
                    7, 7, 10, 12/*mean (0.0424202), correlation (0.405663)*/,
                    12, -5, 12, 9/*mean (0.0942645), correlation (0.410422)*/,
                    6, 3, 7, 11/*mean (0.1074), correlation (0.413224)*/,
                    5, -13, 6, 10/*mean (0.109256), correlation (0.408646)*/,
                    2, -12, 2, 3/*mean (0.131691), correlation (0.416076)*/,
                    3, 8, 4, -6/*mean (0.165081), correlation (0.417569)*/,
                    2, 6, 12, -13/*mean (0.171874), correlation (0.408471)*/,
                    9, -12, 10, 3/*mean (0.175146), correlation (0.41296)*/,
                    -8, 4, -7, 9/*mean (0.183682), correlation (0.402956)*/,
                    -11, 12, -4, -6/*mean (0.184672), correlation (0.416125)*/,
                    1, 12, 2, -8/*mean (0.191487), correlation (0.386696)*/,
                    6, -9, 7, -4/*mean (0.192668), correlation (0.394771)*/,
                    2, 3, 3, -2/*mean (0.200157), correlation (0.408303)*/,
                    6, 3, 11, 0/*mean (0.204588), correlation (0.411762)*/,
                    3, -3, 8, -8/*mean (0.205904), correlation (0.416294)*/,
                    7, 8, 9, 3/*mean (0.213237), correlation (0.409306)*/,
                    -11, -5, -6, -4/*mean (0.243444), correlation (0.395069)*/,
                    -10, 11, -5, 10/*mean (0.247672), correlation (0.413392)*/,
                    -5, -8, -3, 12/*mean (0.24774), correlation (0.411416)*/,
                    -10, 5, -9, 0/*mean (0.00213675), correlation (0.454003)*/,
                    8, -1, 12, -6/*mean (0.0293635), correlation (0.455368)*/,
                    4, -6, 6, -11/*mean (0.0404971), correlation (0.457393)*/,
                    -10, 12, -8, 7/*mean (0.0481107), correlation (0.448364)*/,
                    4, -2, 6, 7/*mean (0.050641), correlation (0.455019)*/,
                    -2, 0, -2, 12/*mean (0.0525978), correlation (0.44338)*/,
                    -5, -8, -5, 2/*mean (0.0629667), correlation (0.457096)*/,
                    7, -6, 10, 12/*mean (0.0653846), correlation (0.445623)*/,
                    -9, -13, -8, -8/*mean (0.0858749), correlation (0.449789)*/,
                    -5, -13, -5, -2/*mean (0.122402), correlation (0.450201)*/,
                    8, -8, 9, -13/*mean (0.125416), correlation (0.453224)*/,
                    -9, -11, -9, 0/*mean (0.130128), correlation (0.458724)*/,
                    1, -8, 1, -2/*mean (0.132467), correlation (0.440133)*/,
                    7, -4, 9, 1/*mean (0.132692), correlation (0.454)*/,
                    -2, 1, -1, -4/*mean (0.135695), correlation (0.455739)*/,
                    11, -6, 12, -11/*mean (0.142904), correlation (0.446114)*/,
                    -12, -9, -6, 4/*mean (0.146165), correlation (0.451473)*/,
                    3, 7, 7, 12/*mean (0.147627), correlation (0.456643)*/,
                    5, 5, 10, 8/*mean (0.152901), correlation (0.455036)*/,
                    0, -4, 2, 8/*mean (0.167083), correlation (0.459315)*/,
                    -9, 12, -5, -13/*mean (0.173234), correlation (0.454706)*/,
                    0, 7, 2, 12/*mean (0.18312), correlation (0.433855)*/,
                    -1, 2, 1, 7/*mean (0.185504), correlation (0.443838)*/,
                    5, 11, 7, -9/*mean (0.185706), correlation (0.451123)*/,
                    3, 5, 6, -8/*mean (0.188968), correlation (0.455808)*/,
                    -13, -4, -8, 9/*mean (0.191667), correlation (0.459128)*/,
                    -5, 9, -3, -3/*mean (0.193196), correlation (0.458364)*/,
                    -4, -7, -3, -12/*mean (0.196536), correlation (0.455782)*/,
                    6, 5, 8, 0/*mean (0.1972), correlation (0.450481)*/,
                    -7, 6, -6, 12/*mean (0.199438), correlation (0.458156)*/,
                    -13, 6, -5, -2/*mean (0.211224), correlation (0.449548)*/,
                    1, -10, 3, 10/*mean (0.211718), correlation (0.440606)*/,
                    4, 1, 8, -4/*mean (0.213034), correlation (0.443177)*/,
                    -2, -2, 2, -13/*mean (0.234334), correlation (0.455304)*/,
                    2, -12, 12, 12/*mean (0.235684), correlation (0.443436)*/,
                    -2, -13, 0, -6/*mean (0.237674), correlation (0.452525)*/,
                    4, 1, 9, 3/*mean (0.23962), correlation (0.444824)*/,
                    -6, -10, -3, -5/*mean (0.248459), correlation (0.439621)*/,
                    -3, -13, -1, 1/*mean (0.249505), correlation (0.456666)*/,
                    7, 5, 12, -11/*mean (0.00119208), correlation (0.495466)*/,
                    4, -2, 5, -7/*mean (0.00372245), correlation (0.484214)*/,
                    -13, 9, -9, -5/*mean (0.00741116), correlation (0.499854)*/,
                    7, 1, 8, 6/*mean (0.0208952), correlation (0.499773)*/,
                    7, -8, 7, 6/*mean (0.0220085), correlation (0.501609)*/,
                    -7, -4, -7, 1/*mean (0.0233806), correlation (0.496568)*/,
                    -8, 11, -7, -8/*mean (0.0236505), correlation (0.489719)*/,
                    -13, 6, -12, -8/*mean (0.0268781), correlation (0.503487)*/,
                    2, 4, 3, 9/*mean (0.0323324), correlation (0.501938)*/,
                    10, -5, 12, 3/*mean (0.0399235), correlation (0.494029)*/,
                    -6, -5, -6, 7/*mean (0.0420153), correlation (0.486579)*/,
                    8, -3, 9, -8/*mean (0.0548021), correlation (0.484237)*/,
                    2, -12, 2, 8/*mean (0.0616622), correlation (0.496642)*/,
                    -11, -2, -10, 3/*mean (0.0627755), correlation (0.498563)*/,
                    -12, -13, -7, -9/*mean (0.0829622), correlation (0.495491)*/,
                    -11, 0, -10, -5/*mean (0.0843342), correlation (0.487146)*/,
                    5, -3, 11, 8/*mean (0.0929937), correlation (0.502315)*/,
                    -2, -13, -1, 12/*mean (0.113327), correlation (0.48941)*/,
                    -1, -8, 0, 9/*mean (0.132119), correlation (0.467268)*/,
                    -13, -11, -12, -5/*mean (0.136269), correlation (0.498771)*/,
                    -10, -2, -10, 11/*mean (0.142173), correlation (0.498714)*/,
                    -3, 9, -2, -13/*mean (0.144141), correlation (0.491973)*/,
                    2, -3, 3, 2/*mean (0.14892), correlation (0.500782)*/,
                    -9, -13, -4, 0/*mean (0.150371), correlation (0.498211)*/,
                    -4, 6, -3, -10/*mean (0.152159), correlation (0.495547)*/,
                    -4, 12, -2, -7/*mean (0.156152), correlation (0.496925)*/,
                    -6, -11, -4, 9/*mean (0.15749), correlation (0.499222)*/,
                    6, -3, 6, 11/*mean (0.159211), correlation (0.503821)*/,
                    -13, 11, -5, 5/*mean (0.162427), correlation (0.501907)*/,
                    11, 11, 12, 6/*mean (0.16652), correlation (0.497632)*/,
                    7, -5, 12, -2/*mean (0.169141), correlation (0.484474)*/,
                    -1, 12, 0, 7/*mean (0.169456), correlation (0.495339)*/,
                    -4, -8, -3, -2/*mean (0.171457), correlation (0.487251)*/,
                    -7, 1, -6, 7/*mean (0.175), correlation (0.500024)*/,
                    -13, -12, -8, -13/*mean (0.175866), correlation (0.497523)*/,
                    -7, -2, -6, -8/*mean (0.178273), correlation (0.501854)*/,
                    -8, 5, -6, -9/*mean (0.181107), correlation (0.494888)*/,
                    -5, -1, -4, 5/*mean (0.190227), correlation (0.482557)*/,
                    -13, 7, -8, 10/*mean (0.196739), correlation (0.496503)*/,
                    1, 5, 5, -13/*mean (0.19973), correlation (0.499759)*/,
                    1, 0, 10, -13/*mean (0.204465), correlation (0.49873)*/,
                    9, 12, 10, -1/*mean (0.209334), correlation (0.49063)*/,
                    5, -8, 10, -9/*mean (0.211134), correlation (0.503011)*/,
                    -1, 11, 1, -13/*mean (0.212), correlation (0.499414)*/,
                    -9, -3, -6, 2/*mean (0.212168), correlation (0.480739)*/,
                    -1, -10, 1, 12/*mean (0.212731), correlation (0.502523)*/,
                    -13, 1, -8, -10/*mean (0.21327), correlation (0.489786)*/,
                    8, -11, 10, -6/*mean (0.214159), correlation (0.488246)*/,
                    2, -13, 3, -6/*mean (0.216993), correlation (0.50287)*/,
                    7, -13, 12, -9/*mean (0.223639), correlation (0.470502)*/,
                    -10, -10, -5, -7/*mean (0.224089), correlation (0.500852)*/,
                    -10, -8, -8, -13/*mean (0.228666), correlation (0.502629)*/,
                    4, -6, 8, 5/*mean (0.22906), correlation (0.498305)*/,
                    3, 12, 8, -13/*mean (0.233378), correlation (0.503825)*/,
                    -4, 2, -3, -3/*mean (0.234323), correlation (0.476692)*/,
                    5, -13, 10, -12/*mean (0.236392), correlation (0.475462)*/,
                    4, -13, 5, -1/*mean (0.236842), correlation (0.504132)*/,
                    -9, 9, -4, 3/*mean (0.236977), correlation (0.497739)*/,
                    0, 3, 3, -9/*mean (0.24314), correlation (0.499398)*/,
                    -12, 1, -6, 1/*mean (0.243297), correlation (0.489447)*/,
                    3, 2, 4, -8/*mean (0.00155196), correlation (0.553496)*/,
                    -10, -10, -10, 9/*mean (0.00239541), correlation (0.54297)*/,
                    8, -13, 12, 12/*mean (0.0034413), correlation (0.544361)*/,
                    -8, -12, -6, -5/*mean (0.003565), correlation (0.551225)*/,
                    2, 2, 3, 7/*mean (0.00835583), correlation (0.55285)*/,
                    10, 6, 11, -8/*mean (0.00885065), correlation (0.540913)*/,
                    6, 8, 8, -12/*mean (0.0101552), correlation (0.551085)*/,
                    -7, 10, -6, 5/*mean (0.0102227), correlation (0.533635)*/,
                    -3, -9, -3, 9/*mean (0.0110211), correlation (0.543121)*/,
                    -1, -13, -1, 5/*mean (0.0113473), correlation (0.550173)*/,
                    -3, -7, -3, 4/*mean (0.0140913), correlation (0.554774)*/,
                    -8, -2, -8, 3/*mean (0.017049), correlation (0.55461)*/,
                    4, 2, 12, 12/*mean (0.01778), correlation (0.546921)*/,
                    2, -5, 3, 11/*mean (0.0224022), correlation (0.549667)*/,
                    6, -9, 11, -13/*mean (0.029161), correlation (0.546295)*/,
                    3, -1, 7, 12/*mean (0.0303081), correlation (0.548599)*/,
                    11, -1, 12, 4/*mean (0.0355151), correlation (0.523943)*/,
                    -3, 0, -3, 6/*mean (0.0417904), correlation (0.543395)*/,
                    4, -11, 4, 12/*mean (0.0487292), correlation (0.542818)*/,
                    2, -4, 2, 1/*mean (0.0575124), correlation (0.554888)*/,
                    -10, -6, -8, 1/*mean (0.0594242), correlation (0.544026)*/,
                    -13, 7, -11, 1/*mean (0.0597391), correlation (0.550524)*/,
                    -13, 12, -11, -13/*mean (0.0608974), correlation (0.55383)*/,
                    6, 0, 11, -13/*mean (0.065126), correlation (0.552006)*/,
                    0, -1, 1, 4/*mean (0.074224), correlation (0.546372)*/,
                    -13, 3, -9, -2/*mean (0.0808592), correlation (0.554875)*/,
                    -9, 8, -6, -3/*mean (0.0883378), correlation (0.551178)*/,
                    -13, -6, -8, -2/*mean (0.0901035), correlation (0.548446)*/,
                    5, -9, 8, 10/*mean (0.0949843), correlation (0.554694)*/,
                    2, 7, 3, -9/*mean (0.0994152), correlation (0.550979)*/,
                    -1, -6, -1, -1/*mean (0.10045), correlation (0.552714)*/,
                    9, 5, 11, -2/*mean (0.100686), correlation (0.552594)*/,
                    11, -3, 12, -8/*mean (0.101091), correlation (0.532394)*/,
                    3, 0, 3, 5/*mean (0.101147), correlation (0.525576)*/,
                    -1, 4, 0, 10/*mean (0.105263), correlation (0.531498)*/,
                    3, -6, 4, 5/*mean (0.110785), correlation (0.540491)*/,
                    -13, 0, -10, 5/*mean (0.112798), correlation (0.536582)*/,
                    5, 8, 12, 11/*mean (0.114181), correlation (0.555793)*/,
                    8, 9, 9, -6/*mean (0.117431), correlation (0.553763)*/,
                    7, -4, 8, -12/*mean (0.118522), correlation (0.553452)*/,
                    -10, 4, -10, 9/*mean (0.12094), correlation (0.554785)*/,
                    7, 3, 12, 4/*mean (0.122582), correlation (0.555825)*/,
                    9, -7, 10, -2/*mean (0.124978), correlation (0.549846)*/,
                    7, 0, 12, -2/*mean (0.127002), correlation (0.537452)*/,
                    -1, -6, 0, -11/*mean (0.127148), correlation (0.547401)*/
            };

}